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Evolutionary Game Theory

In: Handbook of Dynamic Game Theory

Author

Listed:
  • Ross Cressman

    (Wilfrid Laurier University, Department of Mathematics)

  • Joe Apaloo

    (St Francis Xavier University, Department of Mathematics, Statistics and Computer Science)

Abstract

Evolutionary game theory developed as a means to predict the expected distribution of individual behaviors in a biological system with a single species that evolves under natural selection. It has long since expanded beyond its biological roots and its initial emphasis on models based on symmetric games with a finite set of pure strategies where payoffs result from random one-time interactions between pairs of individuals (i.e., on matrix games). The theory has been extended in many directions (including nonrandom, multiplayer, or asymmetric interactions and games with continuous strategy (or trait) spaces) and has become increasingly important for analyzing human and/or social behavior as well. This chapter initially summarizes features of matrix games before showing how the theory changes when the two-player game has a continuum of traits or interactions become asymmetric. Its focus is on the connection between static game-theoretic solution concepts (e.g., ESS, CSS, NIS) and stable evolutionary outcomes for deterministic evolutionary game dynamics (e.g., the replicator equation, adaptive dynamics).

Suggested Citation

  • Ross Cressman & Joe Apaloo, 2018. "Evolutionary Game Theory," Springer Books, in: Tamer Başar & Georges Zaccour (ed.), Handbook of Dynamic Game Theory, chapter 10, pages 461-510, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-44374-4_6
    DOI: 10.1007/978-3-319-44374-4_6
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